2019 PSU R Bootcamp
Welcome to the R Bootcamp for PSU researchers. The goal of this two-day workshop is to provide a broad introduction to the use of the R programming language for social science research. Participants are not expected to have prior experience with R or another programming language. The scope and schedule of the course is provided here.
Bootcamp registration is now closed. See you there!
Instructors
Sy-Miin Chow, Ph.D. Professor of Human Development and Family Studies symiin AT-SIGN psu PERIOD edu http://modslab.org/
Rick O. Gilmore, Ph.D. Professor of Psychology rogilmore AT-SIGN psu PERIOD edu http://gilmore-lab.github.io http://github.com/gilmore-lab/
Michael Hallquist, Ph.D. Assistant Professor of Psychology michael.hallquist AT-SIGN psu PERIOD edu http://dependpsu.weebly.com/
Nilam Ram, Ph.D. Professor of Human Development and Family Studies nilam PERIOD ram AT-SIGN psu PERIOD edu
Mimi Brinberg, M.S. mjb6504 AT-SIGN psu PERIOD edu
Student Coaches
Dan Albohn, dna5021 AT-SIGN psu PERIOD edu Mimi Brinberg, mjb6504 AT-SIGN psu PERIOD edu Kayla Brown, kwb5191 AT-SIGN psu PERIOD edu Meng Chen, mxc681 AT-SIGN psu PERIOD edu Nathan Hall, nate.hall329 AT-SIGN gmail PERIOD com Rebecca Janis, ruj134 AT-SIGN psu PERIOD edu Linying Ji, lzj114 AT-SIGN psu PERIOD edu Jungmin Li, jzl95 AT-SIGN psu PERIOD edu Yanling Li, yxl823 AT-SIGN psu PERIOD edu Jonathan Park, jjp409 AT-SIGN psu PERIOD edu Yiming Qian, yxq5055 AT-SIGN psu PERIOD edu Alicia Vallorani, amvalloranipsu AT-SIGN gmail PERIOD com Holly Zaharchuk, hzaharchuk AT-SIGN psu PERIOD edu
Meeting times and location
Wednesday, August 21, 2019, 9:00 am - 12:00 pm (breakfast 8:30 am) Thursday, August 22, 2019, 9:00 am - 12:15 pm (breakfast 8:30 am) Friday, August 23, 2019, 9:00 am - 4:30 pm (breakfast 8:30 am; lunch 12:15 pm)
library(tidyverse)## ── Attaching packages ──────────── tidyverse 1.2.1 ──## ✔ ggplot2 3.2.1 ✔ purrr 0.3.2
## ✔ tibble 2.1.3 ✔ dplyr 0.8.3
## ✔ tidyr 0.8.3 ✔ stringr 1.4.0
## ✔ readr 1.3.1 ✔ forcats 0.4.0## ── Conflicts ─────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()attendees <- data.frame(day=c("Day 1", "Day 2", "Day 3"), name_badges =c(75, 48, NA))
attendees %>%
ggplot(.) +
aes(x = day, y = name_badges) +
geom_point() +
theme_classic() +
scale_y_continuous(limits = c(0, 100)) +
xlab("") +
theme(axis.text = element_text(size = "1.2em"))## Warning: Removed 1 rows containing missing values (geom_point).## Warning in numnotnull("fontsize"): NAs introduced by coercion
## Warning in numnotnull("fontsize"): NAs introduced by coercion
Meals and beverages in the Moore Building Lobby.
Sessions in 210 & 211 Keller Building
A detailed schedule may be found by following the link.
About this course
R is one of the core languages in data science. It’s free and fun to use. Join us in learning how to use this tool to accelerate your research.
The course heavily emphasizes the use of the RStudio integrated development environment (IDE). You don’t have to use RStudio to use R, but we think that doing so makes R an even more powerful tool. Plus, RStudio has fully featured free versions, including some available entirely in your web browser.
Who’s registered?
Here are some data about the registrants as of 2019-08-23 14:13:01:
We have 115 people registered so far. The following table tells us a bit about them. (These data are generated from the GoogleSheet you completed to register. The data are processed entirely in an R-based workflow that updates automatically every time we regenerate this website.)
# Make table
pos_dept <- xtabs(formula = ~ position + dept, data = rg)
knitr::kable(pos_dept)| BBH | CSD | Ecology | Ed Ldrshp | EESI | HDFS | HHD | IST | Neuro | Prev Ctr | Psych | Span-It-Port | TLT | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Fac | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 0 |
| Grad | 2 | 4 | 1 | 1 | 0 | 17 | 0 | 0 | 1 | 0 | 63 | 2 | 0 |
| Post | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 1 | 0 | 1 | 5 | 0 | 0 |
| Staff | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 6 | 0 | 1 |
| Undergrad | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
What to bring
We ask that you bring an open mind, enthusiasm, and a willingness to ask questions even if they seem trivial. The classrooms we have chosen for the bootcamp have computers with Windows 10, so you do not need to bring your own computer. We will use a standard computing environment set up for your use that takes advantage of the RStudio Server program. This means that RStudio will run in your web browser.
You will need to make sure that you can log on to the PSU system using your Penn State Access ID (e.g., rog1).
Laptop users
If you want to bring your own laptop, please be advised that we will have limited ability to support the installation and use of R on your personal machines. You will want to take the steps outlined here to ensure that your computer can connect to the Penn State wifi. If you want to run RStudio in a web browser, then follow these instructions. Or (or in addition) you may want to install R and RStudio.
Course materials
Here is the GitHub repo where the course files are shared.
We recommend creating a new project inside Rstudio to link with the Github site. This will allow you to ‘pull’ the latest changes to the repository, ensuring that you have the most current materials. Please follow the instructions here.
Acknowledgments
We thank the Department of Psychology, the Department of Human Development & Family Studies (HDFS), Penn State’s Teaching and Learning With Technology (TLT), the Social, Life, & Engineering Sciences Imaging Center (SLEIC), and the Child Study Center’s Open Data and Developmental Science (ODDS) initiative for financial and staff support of the R Bootcamp.